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» A Partition-Based Approach to Graph Mining
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PKDD
2010
Springer
155views Data Mining» more  PKDD 2010»
13 years 6 months ago
Latent Structure Pattern Mining
Pattern mining methods for graph data have largely been restricted to ground features, such as frequent or correlated subgraphs. Kazius et al. have demonstrated the use of elaborat...
Andreas Maunz, Christoph Helma, Tobias Cramer, Ste...
JWSR
2007
114views more  JWSR 2007»
13 years 8 months ago
Development of Distance Measures for Process Mining, Discovery and Integration
: Business processes continue to play an important role in today’s service-oriented enterprise computing systems. Mining, discovering, and integrating process-oriented services h...
Joonsoo Bae, Ling Liu, James Caverlee, Liang-Jie Z...
KDD
2003
ACM
217views Data Mining» more  KDD 2003»
14 years 8 months ago
Algorithms for estimating relative importance in networks
Large and complex graphs representing relationships among sets of entities are an increasingly common focus of interest in data analysis--examples include social networks, Web gra...
Scott White, Padhraic Smyth
SDM
2009
SIAM
149views Data Mining» more  SDM 2009»
14 years 5 months ago
Near-optimal Supervised Feature Selection among Frequent Subgraphs.
Graph classification is an increasingly important step in numerous application domains, such as function prediction of molecules and proteins, computerised scene analysis, and an...
Alexander J. Smola, Arthur Gretton, Hans-Peter Kri...
KDD
2003
ACM
152views Data Mining» more  KDD 2003»
14 years 8 months ago
Interactive exploration of coherent patterns in time-series gene expression data
Discovering coherent gene expression patterns in time-series gene expression data is an important task in bioinformatics research and biomedical applications. In this paper, we pr...
Daxin Jiang, Jian Pei, Aidong Zhang